Search Results - (( initial solution case algorithm ) OR ( java application learning algorithm ))
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Efficiency of heuristic algorithms in solving waste collection vehicle routing problem: a case study
Published 2018“…This paper investigated the efficiency of six heuristic algorithms from prior studies in the attempt to solve issues related to waste collection, namely: (i) Nearest Greedy (NG), (ii) Further from Depot (FFD), (iii) Different Initial Customer (DIC), (iv) Savings Approach, (v) Sweep Algorithm, and (vi) Different Initial Customer based on Sweep Algorithm. …”
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Efficiency of heuristic algorithms in solving waste collection vehicle routing problem: a case study
Published 2018“…This paper investigated the efficiency of six heuristic algorithms from prior studies in the attempt to solve issues related to waste collection, namely: (i) Nearest Greedy (NG), (ii) Further from Depot (FFD), (iii) Different Initial Customer (DIC), (iv) Savings Approach, (v) Sweep Algorithm, and (vi) Different Initial Customer based on Sweep Algorithm. …”
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Simulated annealing algorithm for solving chambering student-case assignment problem
Published 2015“…The objective of the study is to minimize the total completion time for all students in solving the given cases.This study employed a minimum cost greedy heuristic in order to construct a feasible initial solution.The search then is preceded with a simulated annealing algorithm for further improvement of solution quality.The analysis of the obtained result has shown that the proposed simulated annealing algorithm has greatly improved the solution constructed by the minimum cost greedy heuristic. …”
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Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin
Published 2021“…This initial value is often called the “initial guess”. …”
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Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi
Published 2015“…Moreover, fifty four benchmark instances have been modified for this case. The initial feasible solutions have been generated for this purpose. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems
Published 2019“…For the proposed methods, the trial function was employed as an initial approximation to provide more accurate approximate solutions for the considered problems. …”
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Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems
Published 2019“…For the proposed methods, the trial function was employed as an initial approximation to provide more accurate approximate solutions for the considered problems. …”
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A Hybrid ant colony optimization algorithm for solving a highly constrained nurse rostering problem
Published 2019“…Specifically, three main phases were involved in developing the hybrid model, which are generating an initial roster, updating the roster through the ACO algorithm, and implementing the hill climbing to further search for a refined solution. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…However, the HKA algorithm has its own flaws. Although it was introduced as a population-based stochastic optimization algorithm, HKA is not exactly a population-based algorithm because it initializes and updates only a single solution. …”
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Direct solutions of N-th order initial value problems in decomposition series
Published 2023“…In this paper, a class of linear and non-linear nth-order initial value problems (IVPs) is considered. The solutions of these IVPs are obtained by adapting the modified Adomian decomposition method (MADM) as an algorithm for approximating the solutions of the equations in a sequence of time intervals (i.e. time steps). …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar
Published 2015“…The graph theory is used to represent the power system based on interconnection between the buses through the adjacency matrix. The edge reduction algorithm is initially applied to reduce the search space to obtain the initial solution. …”
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A Preliminary Study On Firefly Algorithm Approach For Travelling Salesman Problem
Published 2013“…Each firefly in Firefly Algorithm represents a candidate solution of the Travelling Salesman Problem. …”
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Hybrid fuzzy-sliding mode observer design for estimation and advanced control of an ethylene polymerization process / Jarinah Mohd Ali
Published 2017“…The first case is the known initial state without constraint, which is the ideal case for study or more likely for programming validation purposes. …”
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